Master the complete fundamentals of Machine Learning from data preprocessing to building production ready models
Course Fee: 200 Taka
Enroll Now →Master Python programming essentials for machine learning development.
Learn to work with data using Pandas and prepare it for ML models.
Visualize data insights using Matplotlib, Seaborn, and Plotly.
Prepare data for machine learning models with proper preprocessing techniques.
Learn the core theory behind machine learning and version control with Git and GitHub.
Build models for continuous prediction using regression algorithms.
Build classification models to predict categorical outcomes.
Discover patterns in data without labeled responses.
Combine models for more accurate and robust prediction.
Create and select the most relevant features for your models.
Properly evaluate and validate machine learning models.
Machine Learning
1. Supervised Learning
1.1 Regression
• Linear Regression
• Support Vector Regression (SVR)
1.2 Classification
• Binary Classification
• Multi-class Classification
• Multi-label Classification
• Logistic Regression
• K-Nearest Neighbors (KNN)
• Decision Trees
• Random Forest
• Support Vector Machine (SVM)
• Naive Bayes
• Neural Networks
2. Unsupervised Learning
2.1 Clustering
• K-Means
• Hierarchical Clustering
2.2 Dimensionality Reduction
• PCA
After the initial lessons, the course also covers machine learning theory basics, the model training workflow, and Git/GitHub for version control and collaboration.
Course Fee: 200 Taka
Enroll Now →"I came into this course with basic Python knowledge, but the structured approach to regression and classification models completely transformed my understanding. Building a real house price prediction model in week 6 was a breakthrough moment. Now I can confidently approach any supervised learning problem!"
"The hands-on projects in this course are incredible. From data preprocessing to feature engineering to model deployment - I learned the complete machine learning workflow. The K-means clustering project helped me understand unsupervised learning so well. I've already started my own portfolio projects!"
"The best part about Batch 1 was how the instructors broke down complex algorithms into digestible concepts. Random Forest, SVM, Neural Networks - they all made sense! The model evaluation and validation techniques taught here are exactly what professional data scientists use. I'm very grateful!"
Spaces are limited. Enroll now and start your Machine Learning journey with us.
Course Fee: 200 Taka
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